153 results about "Integral sliding mode" patented technology

The invention relates to a mechanical arm trajectory tracking method based on improved integral terminal sliding mode control, and belongs to the technical field of robot control. According to the method, an integral sliding mode surface and a fast terminal sliding mode surface are combined to create a non-singular fast integral terminal sliding mode surface; an improved index reaching law is designed, and the buffeting problem existing in sliding mode control is weakened. The method comprises the following steps: S1, based on physical parameters of the mechanical arm, establishing a mechanical arm dynamic model by adopting a DH parameter method and a Lagrange dynamics principle; s2, constructing a non-singular fast integral terminal sliding mode surface for the dynamic system; s3, designing an improved reaching law fused with a hyperbolic tangent function; s4, performing trajectory planning by using a Cartesian space interpolation algorithm; s5, integrating the sliding mode surface, the improved reaching law and the dynamical model to derive a trajectory tracking control law; s6, constructing a closed-loop control model of the improved integral terminal sliding mode controller and the mechanical arm system; and S7, the control parameters are adjusted, and mechanical arm trajectory tracking is conducted. The control method serves as a controller to conduct trajectory tracking application on the six-degree-of-freedom mechanical arm. The result shows that on the premise of ensuring finite time convergence, the control method effectively eliminates the buffeting phenomenon of traditional sliding mode control, improves the trajectory tracking precision, has high robustness to external disturbance, and can realize high-precision tracking control of a mechanical arm end effector on a complex trajectory.

The invention discloses a three-level inverter dual-tracking model prediction control method and an inverter, and the method comprises the steps: constructing an integral sliding mode observer, and obtaining a current prediction value and a lumped disturbance estimation value through the integral sliding mode observer; calculating a voltage error of the inverter, and substituting the voltage error into the PI controller to obtain a voltage tracking control item; based on the voltage tracking control term, a switching state that minimizes the cost function is selected to control the inverter. The integral sliding mode observer is configured to calculate a current prediction error between a current prediction value of a current control period and a system output current, introduce an integrator to track the current prediction error, and generate an error function based on an output result of the integrator and the current prediction error. And feeding back a current predicted value and a lumped disturbance estimated value of the next control period through an error function. According to the invention, the method can achieve the quick estimation of the operation state of the inverter and the robust compensation of disturbance, reduces the steady-state tracking error, and reduces the total harmonic distortion of the inverter.

The invention discloses an unmanned ship formation keeping control method under communication time delay, and belongs to the technical field of intelligent ship navigation control, and the method comprises the steps: building an unmanned ship motion model based on a built unmanned ship three-degree-of-freedom motion model, a state-space equation of the unmanned ship three-degree-of-freedom motion model, and an environment disturbance mathematical model; aiming at the problems of wind wave flow disturbance and communication time delay suffered by the unmanned ship formation, constructing a superhelix integral sliding mode observer and a self-adaptive time delay estimator; a formation control system is built by combining a fixed time theory, a formation controller of a nonsingular terminal sliding mode and a superhelix integral sliding mode observer, and formation keeping of the unmanned surface vehicle is achieved; and finally verifying through a simulation experiment. The formation control system is built based on the fixed time theory and the nonsingular terminal sliding mode control method for the unmanned surface vehicle formation, the unmanned surface vehicle formation control precision is effectively improved, unmanned surface vehicle formation shape keeping control under composite disturbance is achieved, and the method has great significance in promoting precise development of unmanned surface vehicle formation operation.

The invention relates to the technical field of motor control, in particular to a control and parameter intelligent optimization method for an anti-impact high-precision PMSM (permanent magnet synchronous motor) feeding servo system, which comprises the following steps of: S1, establishing a physical structure and a dynamic model of a PMSM driving feeding system; s2, designing a variable gain fractional order super-spiral sliding mode controller VGFSTSMC, realizing finite time convergence of position tracking errors by dynamically adjusting and controlling gain coefficients, and inhibiting system jitter; s3, designing an adaptive sliding mode disturbance observer ASMDO, and estimating and compensating unknown disturbance in real time through adaptive gain adjustment and an integral sliding mode surface; s4, identifying a system Stribeck friction model based on a least square method, and inputting the system Stribeck friction model as a friction feedforward compensation FFC to a current loop to reduce the disturbance uncertainty of the system; s5, dynamically adjusting and optimizing control parameters of the VGFSTSMC and the ASMDO by adopting an optimization algorithm so as to minimize a root-mean-square value RMSE of a position tracking error and a maximum instantaneous error; and S6, VGFSTSMC, ASMDO and FFC are combined with an optimization algorithm, and the PMSM is driven to realize high-precision position control.

The invention discloses an underwater vehicle tracking control method with state constraint under input saturation. The method comprises the following steps: firstly, constructing an AUV control system containing model uncertainty and unknown interference based on a kinematics model and a dynamics model of the AUV, and obtaining a reference trajectory of a tracking target; establishing an error model of the AUV control system in combination with the error conversion function, and obtaining a design variable related to the position tracking error; meanwhile, deducing a design variable related to a speed tracking error; constructing a fixed time integral sliding mode lumped disturbance observer based on a design variable related to a position tracking error; and finally, combining a fixed time integral sliding mode lumped disturbance observer and design variables related to a speed tracking error to construct a trajectory tracking control system, and designing a fixed time convergence sliding mode controller by using a continuous input signal and a position and speed adaptive law. According to the invention, the tracking error is stabilized to zero in a fixed time; and continuous control input is realized.

The invention discloses a finite-time active-disturbance-rejection control method for a multi-unmanned-aerial-vehicle hanging transportation system. According to the finite-time active-disturbance-rejection control method, a finite-time super-spiral sliding-mode observer is used for carrying out observation compensation on load errors and lumped disturbance of the load errors, a finite-time sliding-mode controller is constructed, total tension for controlling load movement is determined, and an optimal tension distribution scheme is solved. External disturbance is introduced, a load is taken as a virtual leader, a leader following cluster model is constructed, a finite time reduced-order proportional differential observer and a finite time controller are designed, formation finite time control is carried out, and an expected trajectory of each unmanned aerial vehicle is determined; an actuator fault model and a virtual control quantity are introduced, an unmanned aerial vehicle dynamics model is constructed, and a lumped disturbance reconstruction state error system is introduced; and designing a finite-time reduced-order generalized parameter estimation observer and a finite-time nonsingular terminal integral sliding mode fault-tolerant controller, carrying out unmanned aerial vehicle position loop control and attitude loop control, and realizing finite-time active-disturbance-rejection control of the multi-unmanned aerial vehicle hanging transportation system.

The invention relates to the technical field of mining permanent magnet synchronous motor sensorless control, and particularly discloses a composite sliding mode control and adaptive phase-locked loop collaborative optimization method. Aiming at the technical bottlenecks of a traditional control strategy in the aspects of rotating speed fluctuation suppression, load disturbance compensation and rotor position observation precision, a collaborative architecture of a time-varying integral terminal sliding mode control module, a sliding mode disturbance observation module and a self-adaptive phase-locked loop module is constructed, so that the dynamic performance optimization of the system is realized. According to the method, through the dynamic coupling design of the time-varying gain nonlinear reaching law and the fast integral terminal sliding mode surface, the convergence speed and the buffeting suppression requirement are balanced while the disturbance dynamic influence is eliminated; multi-dimensional decoupling observation of external load disturbance is realized based on a hierarchical disturbance observer architecture, and a disturbance real-time suppression path is established in combination with a feed-forward compensation strategy; and constructing an error self-adaptive correction mechanism of rotor position observation by dynamically adjusting a phase-locked loop proportionality coefficient and a phase compensation parameter. The limitation of parameter solidification and observation coupling in traditional control is broken through, the rotating speed tracking stability, the position observation precision and the anti-interference capability under complex working conditions are remarkably improved, and an innovative solution is provided for a high-precision servo driving system.

A motor control method based on an improved composite reaching law and a sliding mode observer belongs to the technical field of permanent magnet synchronous motor system control, and comprises the following steps: firstly, considering motor internal parameter change and external load disturbance, and establishing a disturbance-containing permanent magnet synchronous motor mathematical model and a motor state equation; secondly, providing a new switching function, constructing an improved composite reaching law, completing stability proving, and analyzing rapid convergence and buffeting suppression capability of the improved composite reaching law; then constructing an anti-saturation integral sliding mode surface, and designing a sliding mode speed controller according to the permanent magnet synchronous motor mathematical model containing disturbance, the anti-saturation integral sliding mode surface and the improved composite reaching law; and finally, aiming at disturbance in the controller, designing an improved sliding mode disturbance observer, and completing stability proving. The contradiction between fast convergence and buffeting suppression in an existing sliding mode reaching law scheme is solved, and the provided improved sliding mode observer improves the observation precision and the response speed.

The invention discloses a terminal sliding mode control method based on an arc tangent function and application of the terminal sliding mode control method. The traditional terminal sliding mode control is fast in convergence, but has a singular problem. The traditional nonsingular terminal sliding mode control solves the singular problem at the cost of sacrificing the convergence time. Therefore, the arc tangent function and the power function are introduced on the basis of the terminal sliding mode, the novel non-singular fast terminal sliding mode control method is constructed, and compared with a traditional terminal sliding mode control method, the method is continuous at a balance point, the singular problem is solved, and the method has the advantages that the method is simple and convenient to operate. Compared with the traditional linear sliding mode control, integral sliding mode control and nonsingular terminal sliding mode control, the method ensures that the speed regulation system has higher convergence speed, higher tracking precision and stronger anti-interference performance.

According to the continuous self-adaptive integral sliding mode leader-following multi-robot affine formation control method based on the event triggering mechanism, distributed control and affine formation strategies are fused, a formation controller with high maneuverability and high robustness is constructed, the event triggering mechanism is introduced to reduce the communication load and the control frequency, and the control efficiency is improved. The method belongs to the technical field of multi-robot intelligent cooperative control. Aiming at the common problem of insufficient formation rigidity and flexibility in a multi-robot formation control task, the invention provides a cooperative control method capable of realizing various affine transformations such as zooming, rotating, shearing, coplanar and collinear, and the cooperative control method has good environmental adaptability and system performance.

The invention provides a finite time cooperative tracking control method based on an adaptive RBF neural network, and belongs to the technical field of networked multi-agent control strategies. Constructing a dynamic mathematical model of a high-order all-drive uncertain nonlinear multi-agent system comprising a virtual leader and a follower; according to a cooperative tracking control target and uncertain items in the system, constructing an error dynamic system comprising an adaptive RBF neural network estimation compensation item; designing a finite time integral sliding mode surface based on a high-order all-drive system theory; designing linearization parameters of a finite time integral sliding mode surface based on a pole assignment method according to system dynamic performance and finite time convergence requirements, and obtaining a finite time integral sliding mode controller; and designing a self-adaptive updating law of an upper bound of an RBF neural network weight and an approximate error, and substituting the network weight and the approximate error into a finite time integral sliding mode controller to realize cooperative tracking control of finite time.

The invention provides an FTESO-based parallel inverter system recursive nonsingular terminal sliding mode control method, and the method comprises the following steps: firstly, designing FTESO to estimate system load disturbance; and secondly, designing an RNTSM control law for the inverter system based on FTESO compensation, so that the inverter system can completely overcome the influence of load interference, and the robustness of filtering parameter perturbation is enhanced. According to the method, the recursive terminal sliding mode surface formed by combining the non-singular fast terminal sliding mode and the integral sliding mode is adopted, it can be ensured that the output voltage of an inverter system rapidly tracks the reference voltage of the inverter system within finite time, and system buffeting is effectively weakened.

The invention discloses a permanent magnet synchronous motor control method of an adaptive fractional order fast terminal sliding mode. The method comprises the following steps: firstly, constructing a mathematical model of the permanent magnet synchronous motor in a d-q axis rotor rotating coordinate system; then designing a fractional order fast terminal sliding mode surface, and solving an equivalent control law of sliding mode control based on the designed fractional order fast terminal sliding mode surface; performing adaptive design on the switching control gain and the boundary layer thickness to obtain an adaptive switching control law; and integrating the equivalent control law and the adaptive switching control law to obtain a total control law. Compared with existing surface-mounted permanent magnet synchronous motor sliding mode control, the surface-mounted permanent magnet synchronous motor sliding mode control method introduces a fractional order fast terminal sliding mode surface on the basis of a traditional integral sliding mode so as to reduce system buffeting and ensure that tracking errors converge in finite time, and meanwhile designs a self-adaptive control law of switching control rate gain and boundary layer thickness. The uncertainty influence of external disturbance is counteracted, and the robustness of the system is improved.

The invention discloses a self-adaptive cooperative control strategy based on a variable speed reaching law and a neural network, belongs to the field of intelligent control, and mainly aims at estimating and compensating uncertainty, external disturbance and actuator saturation existing in a queue in queue control and improving the stability, robustness and control performance of the whole queue. The method comprises the following steps: establishing a queue system model with uncertainty, external disturbance and actuator saturation; establishing a Gaussian error function approximation strategy; establishing a tracking error; establishing a variable speed reaching law; establishing a queue integral sliding mode error; establishing a queue coupling sliding mode error; establishing an adaptive parameter estimation mechanism for external disturbance and Gaussian function approximation errors in the queue; establishing a neural network estimation mechanism for uncertainty in the queue; and establishing a queue integral sliding mode control strategy based on a variable speed reaching law, a Gaussian error function approximation strategy, an adaptive parameter estimation mechanism and a neural network estimation mechanism. The method is used for queue cooperative intelligent control.

The invention relates to the technical field of closed-loop drift control, and particularly discloses a closed-loop drift control method and system for an autonomous vehicle in an uncertain environment, and the method comprises the steps: building a vehicle kinematic model based on a Frenet coordinate system, and constructing an MPC path tracking controller with a preview mechanism; establishing a three-degree-of-freedom vehicle dynamics model with additional yawing moment; the method comprises the following steps: establishing a UniTile-Ctrl tire dynamic model; designing a robust drift controller by combining LQR and integral sliding mode control on the basis of the whole vehicle dynamic model and the tire dynamic model, designing a torque distribution module by taking minimization of distribution error and tire load utilization rate as targets on the basis of ideal rear wheel rotating speed and additional yawing moment output by the robust controller, and outputting a torque distribution model; according to the drifting vehicle tracking control method, closed-loop drifting control can be achieved, the drifting vehicle tracking control performance and robustness are improved, and safety guarantee is provided for limit control over the uncertain road surface of the vehicle.

The invention discloses a permanent magnet synchronous motor control method based on self-tuning prediction and a neural network, which aims at the inductance parameter mismatch problem in incremental dead-beat prediction control, adopts an inductance mismatch diagnosis and self-tuning mechanism to dynamically adjust model parameters and weight coefficients, and improves the robustness and dynamic response performance of a current loop. A neural network sliding mode control method is introduced into a speed ring, adaptive compensation of nonlinear disturbance and parameter uncertainty is realized by constructing an integral sliding mode surface and adjusting a sliding mode gain on line, and a stable and reliable current control instruction is output; meanwhile, the observer part constructs an improved super-spiral sliding-mode observer, the electrical angle and d-q axis composite disturbance can be estimated in real time with high precision, effective compensation information is provided for current control, and the overall stability and robustness of the system are further enhanced.

The invention discloses a multi-agent sliding mode safety control method based on dynamic event triggering under hybrid network attack, and the control method comprises the following steps: building a multi-agent system model comprising spoofing attack and DoS attack; in order to cope with hybrid network attacks, an integral sliding mode surface function is constructed, an online estimation method is provided, and an unknown network attack mode can be estimated in real time in the absence of prior information; a novel self-adaptive sliding mode controller is developed, and the accessibility of a preset sliding mode surface is ensured; by introducing an auxiliary variable, a dynamic and static event triggering mechanism in the framework is considered, so that the use of communication resources is minimized; a Lyapunov stability theory and a finite time method are utilized to analyze the convergence of the multi-agent system under the control strategy. According to the control method provided by the invention, the influence of spoofing attack and DoS attack on the system can be eliminated, so that the state of the multi-agent system is consistent within finite time.

The invention discloses a flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, and belongs to the field of flexible joint mechanical arm control, and the method comprises the following steps: S1, building a flexible joint mechanical arm dynamic model containing uncertain composite disturbance, and decoupling the model into a slow variable subsystem and a fast variable subsystem; s2, estimating lumped matching disturbance in the slow varying subsystem by using a compensation function observer; s3, constructing an integral sliding mode surface and a self-adaptive reaching law with dead zone correction for the slow-varying subsystem; designing a linear quadratic regulator for the quick-change subsystem, defining a performance index, and solving a Riccati equation to obtain an optimal control law; s4, superposing the slow-varying subsystem control law and the fast-varying subsystem control law to obtain integral control input; and S5, performing simulation verification. By adopting the flexible joint mechanical arm AISMC compensation control method under singular perturbation decomposition, trajectory tracking precision, robustness and stability are considered, and the method has a wide application prospect.

The invention belongs to the technical field of robot control, and discloses a visual servo intelligent robust control method for a mobile mechanical arm for a complex operation task, which comprises the following steps of: 1, acquiring a working scene image, and calculating a space coordinate of a target feature point in real time through a projection transformation model; step 2, dynamically inhibiting visual measurement noise by adopting adaptive Kalman filtering, generating a feedforward compensation signal through an integral sliding mode observer, and decoupling chassis slippage disturbance; step 3, inputting the pose signal into a radial RBF neural network, designing an RBF gain scheduler, and adjusting an output proportion-integral gain in real time to suppress external time-varying disturbance; 4, adopting a hybrid visual servo mode switching mechanism, and generating a mobile platform control instruction through an integral sliding mode surface in a position servo mode; and 5, designing a three-order composite controller to drive the mechanical arm so as to realize accurate grabbing. According to the method, the grabbing deviation caused by kinematics uncertainty of the mobile platform and dynamic environment disturbance is eliminated.

The invention relates to the technical field of motor control, in particular to an integral self-adaptive observer method for permanent magnet synchronous motor sensorless control, which comprises the following steps of: 1, taking a surface-mounted permanent magnet synchronous motor as a research object, selecting a two-phase static coordinate system under a two-phase static coordinate system, the error i between the actual value and the estimated value of the stator current is a state variable; 2, designing a finite time integral sliding mode function s, and enabling the system to converge in finite time; a smooth H (i) function is designed, the function weakens buffeting caused by constant high switching gain, a finite time integral sliding mode function is further provided, a fuzzy rule is designed to adjust back electromotive force feedback gain, the sine degree of back electromotive force is made to be better, the estimation performance of the rotor position and speed is improved, and the method is suitable for large-scale popularization and application. And the accurate observation performance is still kept under the complex working condition.

The invention relates to a permanent magnet synchronous motor control method and system based on a sliding mode variable structure. The method comprises the following steps: constructing a current state equation of a surface-mounted permanent magnet synchronous motor under a two-phase static coordinate system; designing a sliding-mode observer according to the current state equation; designing an integral type sliding mode control rate through a sliding mode observer and a non-singular fast terminal sliding mode surface, and replacing a sign function of the integral type sliding mode control rate with a sine saturation function with a variable boundary layer; designing a back electromotive force adaptive rate, and combining the back electromotive force adaptive rate with an integral sliding mode control rate to form an adaptive nonsingular fast terminal sliding mode observer; using the observed back electromotive force of the permanent magnet synchronous motor as the input of a PID phase-locked loop, and using the PID phase-locked loop to observe the rotor position and the rotating speed of the permanent magnet synchronous motor; and feeding back the rotor position and the rotating speed of the permanent magnet synchronous motor observed by the PID phase-locked loop to a rotating speed loop of a permanent magnet synchronous motor control system to realize closed-loop control.

The invention discloses a permanent magnet synchronous motor model-free quasi-resonance sliding mode control method and system. The method comprises the following steps: S1, establishing a model-free quasi-resonant sliding mode current controller which is configured with an input and output hyper-local model based on motor control and is a function of a primary time derivative of an output variable relative to a control variable and unknown disturbance; setting an integral sliding mode surface with a quasi-resonance term, and obtaining a control law of the control variable in combination with the hyper-local model; s2, setting an extended state observer which is connected with the model-free quasi-resonance sliding mode current controller and is used for observing the unknown disturbance controlled by the motor and applying the unknown disturbance to a control law of the control variable; and S3, obtaining an observation value of an output variable, and obtaining a value of a control variable applied to motor control according to the control law of the control variable. The model-free quasi-resonance sliding mode control system comprises the model-free quasi-resonance sliding mode current controller and an expansion state observer. The speed fluctuation is reduced, and the torque output quality is improved.

The invention discloses a TBM cutterhead main drive intelligent decision-making method and system, and belongs to the technical field of cutterhead drive control. Unified regulation and control and target torque distribution of a driving system are realized by constructing a master-slave type multi-driving-unit collaborative architecture; a fault is identified by monitoring a current signal, a voltage vector is reconstructed according to the fault type, and continuous and stable output under the fault is ensured; a disturbance observation method based on an integral sliding mode is provided, and control deviation caused by system disturbance and parameter changes is dynamically estimated and compensated; an MPTA control strategy of high-frequency virtual signal injection is designed, and utilization of reluctance torque and stable tracking of an MTPA working point are achieved; the torque output capacity of a fault unit and the torque margin of a healthy unit are comprehensively considered, a load distribution strategy is planned, and the overall loading capacity and the operation life of the driving system are improved.

The invention discloses a multi-vector model predictive control method for a dual three-phase permanent magnet synchronous generator considering a harmonic space, which comprises the following steps: selecting three voltage vectors to construct a target voltage vector in each control sector, substituting the target voltage vector into a discrete predictive control model to obtain a predictive current at the next moment, and further constructing a value function to obtain a predictive current at the next moment; and selecting an optimal virtual voltage vector set of the two subspaces and action time of the optimal virtual voltage vector through a minimum value function, combining control of the two subspaces into a control period, recalculating a switching sequence PWM signal, and acting on the rectifier. In the process of selecting the optimal virtual voltage vector set of the two subspaces, a superhelix integral sliding mode observer is used for observing current disturbance, and a composite controller is used for conducting zero static error tracking on harmonic waves in the z1z2 subspace. Under the condition that the dynamic performance is not affected, the fundamental wave space control performance is improved, the harmonic current is suppressed, and the steady-state performance of the DTP-PMSG is improved.

The invention relates to the technical field of motor driving, and discloses a brushless motor non-inductive FOC driving method and device, and the method comprises the steps: collecting a first three-phase stator current and a bus voltage of a brushless motor, and calculating a rotor position estimation value; performing coordinate transformation on the first three-phase stator current to obtain a first d-axis actual current and a first q-axis actual current, and calculating a first d-axis current error and a first q-axis current error; calculating a d-axis first-order integral value, a d-axis double-integral accumulated value, a q-axis first-order integral value and a q-axis double-integral accumulated value, and constructing a d-axis double-integral sliding mode surface and a q-axis double-integral sliding mode surface; according to the method, a d-axis compensation voltage instruction is generated based on the d-axis double-integral sliding mode surface, a q-axis compensation voltage instruction is generated based on the q-axis double-integral sliding mode surface, the d-axis compensation voltage instruction and the q-axis compensation voltage instruction are applied to the brushless motor, the problem of magnetic field orientation deviation caused by position estimation lag in non-inductive FOC driving is solved, and the output efficiency of the motor is improved.

The invention discloses a fixed time inclusion control method and system for a second-order nonlinear multi-agent system, and the method comprises the steps: defining a state tracking error according to a control target, augmenting the state tracking error into a matrix form, and designing an integral sliding mode surface for suppressing disturbance; designing a distributed fixed time inclusion consistency protocol and a dynamic event triggering mechanism based on position information and speed information according to the integral sliding mode surface; and controlling the multi-agent system model to reach an integral sliding mode surface according to a distributed fixed time inclusion consistency protocol and a dynamic event triggering mechanism, then sliding on the integral sliding mode surface, and controlling the state of the multi-agent system model to realize inclusion consistency within fixed time. According to the invention, the energy consumption of the system and the updating frequency of the controller can be reduced, the service life of the system is prolonged, and under a new distributed fixed time inclusion consistency protocol, the system firstly reaches the sliding mode surface and then slides on the sliding mode surface, so that the inclusion consistency of the system state is finally realized within fixed time.

A wind power generation system preset time maximum power point tracking control method comprises the following steps: firstly, establishing a wind power generation system dynamic model containing parameter uncertainty and external disturbance, and meanwhile, constructing a preset time convergence integral sliding mode surface; the method has the core advantages that the convergence time can be directly set by controller parameters and is irrelevant to the initial state of the system; secondly, designing a preset time self-adaptive controller based on the rotating speed tracking error and the sliding mode surface, and enabling the rotating speed tracking error to be quickly converged in preset time; the upper bound of lumped uncertainty of the system is estimated online through a self-adaptive mechanism, unknown dynamic and external disturbance are compensated in a unified mode, and dependence on an accurate model and disturbance prior knowledge is not needed; and finally, strictly proving the preset time stability of the closed-loop system through a Lyapunov stability theory. The method has good dynamic response performance and predictable convergence behaviors, and the robustness and the power generation efficiency of the system are improved.

The invention discloses an intelligent automobile stability control system based on tire cornering stiffness estimation. The intelligent automobile stability control system comprises a driver-vehicle-road comprehensive information acquisition module, a control variable expected value calculation module, a target stabilizing moment calculation module and a moment distribution mode selection module. According to the invention, information acquired by a driver-vehicle-road comprehensive information acquisition module is utilized to calculate a tire cornering stiffness mutation factor and selectively start a tire cornering stiffness dynamic estimator based on a depth deterministic strategy gradient algorithm, so that a control variable expected value is accurately calculated; and calculating a target stable moment by using an adaptive fuzzy integral sliding mode algorithm, and determining a moment distribution mode according to the numerical values of the three factors and a moment distribution mode selection rule. According to the method, the tire cornering stiffness can be estimated in time according to the sudden change degree of the tire cornering stiffness, and the transverse stability control effect of the electric automobile is guaranteed.

The invention discloses an interchange intelligent motorcade sliding mode control method considering disturbance and actuator saturation. The method comprises the following steps: respectively constructing three-order dynamic models considering disturbance and actuator saturation; establishing an intelligent network connection vehicle following model considering the expected speed of the road section in the interchange area, and combining a vehicle position tracking error and a speed error to construct an integral sliding mode surface and generate a coupling sliding mode surface; constructing a non-linear disturbance observer on the basis of the three-order dynamic model considering disturbance to generate a disturbance observation value; constructing an auxiliary dynamic system on the basis of the three-order dynamic model considering the saturation of the actuator to generate an auxiliary signal; in order to realize a motorcade control target, a motorcade controller is designed in combination with a coupling sliding mode surface, a disturbance observation value and an auxiliary signal to control the motion state of vehicles in the intelligent network connection motorcade, so that the driving of the intelligent network connection motorcade in an interchange area conforms to a traffic flow theory, and the consistency of the positions and the speeds of the vehicles in the motorcade and the stability of a motorcade string are ensured.

The present invention discloses an unmanned ship adaptive path tracking control method, device, equipment and medium. The method comprises: establishing a dynamic model of an unmanned ship without parameter requirements, determining dynamic characteristics according to a simplified dynamic model of the directional force of the propeller of the unmanned ship, wherein the dynamic characteristics include unmodeled dynamic characteristics; fitting dynamic characteristics to the unmodeled dynamic characteristics through an RBF neural network; determining an integral sliding surface by using a preset construction method to determine the integral sliding surface by using a swell velocity error and a bow roll angle error; adaptively calculating the integral sliding surface to determine an adaptive rate, adaptively updating the fitted dynamic characteristics according to the adaptive rate, and obtaining real-time fitted dynamic characteristics; determining a real-time target thrust according to real-time swell and bow roll direction speeds and real-time fitted dynamic characteristics, and controlling the propeller motor according to the target thrust. The problem of being unable to effectively track and control the adaptive path of an unmanned ship can be solved by implementing the method of the present invention.